构建了全球最大比特币交易图数据集，支持深度研究与分析。
Bitcoin Research with a Transaction Graph Dataset
- 构建25200万节点、78500万边的比特币交易图，覆盖13年历史数据。
- 提供超10万地址标签数据，用于实体类型识别与分类任务。
- 开源全部数据与代码，适合区块链分析、图神经网络研究者使用。
比特币由中本聪于2008年推出，建立了一个无需中心化机构即可存储和转移价值的去中心化数字经济。本文提出一个大规模交易图数据集，包含25200万节点和78500万边，覆盖近13年、6.7亿笔交易，所有节点与边均带时间戳。针对监督任务，提供了两个标注数据集：其一为3.3万个节点按实体类型标注，其二为近10万个比特币地址附带实体名称与类型标签。该数据集是目前公开可用的最大比特币交易数据集，旨在推动该领域的高级研究，克服现有数据集的局限性。本文还训练多种图神经网络模型以预测节点标签，为未来研究建立基线。此外，展示了多个应用场景，证明该数据集在比特币分析之外的适用性。所有数据与源代码均已公开，确保结果可复现。
原文摘要 · Abstract (English)
Bitcoin, launched in 2008 by Satoshi Nakamoto, established a new digital economy where value can be stored and transferred in a fully decentralized manner - alleviating the need for a central authority. This paper introduces a large scale dataset in the form of a transactions graph representing transactions between Bitcoin users along with a set of tasks and baselines. The graph includes 252 million nodes and 785 million edges, covering a time span of nearly 13 years of and 670 million transactions. Each node and edge is timestamped. As for supervised tasks we provide two labeled sets i. a 33,000 nodes based on entity type and ii. nearly 100,000 Bitcoin addresses labeled with an entity name and an entity type. This is the largest publicly available data set of bitcoin transactions designed to facilitate advanced research and exploration in this domain, overcoming the limitations of existing datasets. Various graph neural network models are trained to predict node labels, establishing a baseline for future research. In addition, several use cases are presented to demonstrate the dataset's applicability beyond Bitcoin analysis. Finally, all data and source code is made publicly available to enable reproducibility of the results.
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